Browsing by Author "Ceylan, Sude Dila"

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Application of Meta-heuristic Algorithms for Sequencing Multi-model Assembly Line with Sequence-Dependent Setup Time in Garment Industry
(Springer Science and Business Media Deutschland GmbH, 2024) Tunahan Kuzu; Yaren Can; Elvin Sarı; Devin Duran; Sude Dila Ceylan; Mert Paldrak; Mustafa Arslan Ornek; Sarı, Elvin; Ceylan, Sude Dila; Can, Yaren; Örnek, Mustafa Arslan; Kuzu, Tunahan; Duran, Devin; Paldrak, Mert; N.M. Durakbasa , M.G. Gençyılmaz
This study provides an overview of the definition of long setup times and lateness due to the wide variety of models produced in the garment industry the solutions developed to solve these problems and the designs to be proposed. The setup times of the product produced in the Multi-Model Assembly Line vary according to the model type. In this study we considered a single machine as an assembly line and adapted Single Machine Scheduling with Sequence-Dependent setup times problem to Multi-Model Assembly Line Sequencing with sequence-dependent setup times problem for the garment industry. To solve this problem we used two different solution techniques: Meta-Heuristic Algorithms and a mathematical model that includes the setup process and lateness accordingly suggested. Two different metaheuristic algorithms Tabu Search and Simulated Annealing were used in this paper. SA algorithm Tabu Search Algorithm and mathematical model were used to find optimal and near-optimal results which were compared. The metaheuristic achieved favourable solutions when comparing the results with mathematical model results. The mathematical model suggested was solved utilizing version 20.1 of ILOG CPLEX OPTIMIZATION STUDIO. The simulated Annealing and Tabu Search algorithm suggested were solved utilizing version R2023a of MATLAB. The obtained results are compared with respect to solution quality and computational time. © 2024 Elsevier B.V. All rights reserved.
Fuzzy Goal Programming Model for Sequencing Multi-model Assembly Line with Sequence Dependent Setup Times in Garment Industry
(Springer Science and Business Media Deutschland GmbH, 2023) Elvin Sarı; Mert Paldrak; Tunahan Kuzu; Devin Duran; Yaren Can; Sude Dila Ceylan; Mustafa Arslan Ornek; Başak Erol; Sarı, Elvin; Ceylan, Sude Dila; Can, Yaren; Kuzu, Tunahan; Duran, Devin; Paldrak, Mert; Erol, Başak; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
In today’s competitive market the pressure on organizations to find ways to create value for customers and meet their requirements becomes stronger. In this manner clothing manufacturers focus on the production of various products with low stock to minimize their costs. In the garment industry assembly lines are commonly used production systems whose balance is the main concern of production managers. Meeting customer demand on-time is of outsized importance for the reputation of a clothing manufacturer and several objective functions must be considered simultaneously. In this study two objective functions namely minimization of setup times and minimization of lateness are handled to increase the efficiency of the assembly line and convenience to customers. A real-life problem in the garment industry is defined and formulated as a Fuzzy Goal Programming model since the aspiration levels of each objective are not certainly known. Two different Weighted Fuzzy Goal Programming Models are proposed and the proposed mathematical models are tackled with the help of ILOG IBM CPLEX OPTIMIZATION STUDIO version 20.1 and the solutions are interpreted from a decision-maker perspective. © 2023 Elsevier B.V. All rights reserved.
Intelligent Benders’ Decomposition Algorithm for Sequencing Multi-model Assembly Line with Sequence Dependent Setup Times Problem: A Case Study in a Garment Industry
(Springer Science and Business Media Deutschland GmbH, 2023) Elvin Sarı; Mert Paldrak; Yaren Can; Tunahan Kuzu; Sude Dila Ceylan; Devin Duran; Mustafa Arslan Ornek; Ozan Can Yıldız; Sarı, Elvin; Ceylan, Sude Dila; Can, Yaren; Kuzu, Tunahan; Duran, Devin; Paldrak, Mert; Yıldız, Ozan Can; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
In recent years clothing manufactures aim at producing various of products with low stock in order to meet customer demand. Besides this fact the ready-made clothing industry needs to pursue science technology and innovation policies to keep up with the rapid change in the fashion industry. One of the most commonly used production systems in garment industry is assembly lines where parts are subsequently added until the end product is obtained. In garment industry on time delivery plays a vital role in increasing customer satisfaction while ensuring demand. Consequently setup times in assembly lines are of paramount importance to track the performance of production system. In this study the minimization problem of long setup times due to the wide variety of models produced in the garment industry is handled. A real-life production management problem is defined formulated as an MIP model and solved to improve customer delivery rate and to increase efficiency by minimizing setup time. To solve this problem to optimality two exact solution techniques namely Branch and Bound and Benders’ Decomposition Techniques are taken into consideration. The proposed mathematical model is solved with ILOG CPLEX OPTIMIZATION STUDIO version 20.1 and the solutions obtained using each technique are compared with respect to solution quality and computational time. © 2023 Elsevier B.V. All rights reserved.